A study of early predictors (Comorbidities and Etiology) of patient’s outcome after cirrhosis hospitalization

Group 19

Eva Frossard, Pauline Charpentier, Noy Tabul, Fabian Ziegler

Introduction

Objective: Understand patterns and correlations between early predictors Comorbidities and Etiologies, their numerical estimate CPS and Charlson index and cirrhosis’ patients outcome  

Cirrhosis = condition in which the liver is scarred and permanently damaged.

How is this study relevant ?

Graph eva BioRender explaining the relatins between the index, etiologies…

Materials - Dataset

Data set used: Early predictors of outcomes of hospitalization for cirrhosis and assessment of the impact of race and ethnicity at safety-net hospitals

  • 733 patients
  • From 4 safety-net hospitals in the US
  • Male dominated study (67.31%)
  • Predominant age group [60; 70]
  • Main liver disease diagnosis
  • Ascites ()

Methods

Cleaning:

  • Started by extracting necessary columns

  • Adding an ID column as a unique identifier for each observation

  • Renamed columns, reordered them, and assigned classes to etiology and comorbidities.

tidying:

Augmenting:

  • Created categories for Mortality: no death, death in hospital, after 30 days, after 90 days.

  • Creating age bins instead decade

Overview of comorbidities and etiologies

  • Etiology is the study of the factors that come together leading to a disease.

  • Comorbidity is an additional disease that can interact and coexist simultaneously with cirrhosis.

Liver disease repartition in cirrhosis patients, stratified by mortality

Model 1

Model 2

Death ratios of every Etiology/Liver disease combination

Conclusion